METHODS FOR ESTIMATING THE PROBABILITY OF BANK DEFAULT
Table of contents
Share
Metrics
METHODS FOR ESTIMATING THE PROBABILITY OF BANK DEFAULT
Annotation
PII
S042473880000616-6-1
Publication type
Article
Status
Published
Authors
Anatoly Peresetsky 
Edition
Pages
37-62
Abstract
The results of an econometric analysis of Russian Bank defaults in 1997-2013 are presented. The main goal of the study is to find out how publicly available information from banks ' balance sheets can be used to predict Bank defaults. It is shown that preliminary expert clustering of banks, as well as accounting for the macroenvironment, improve the quality of default models. Heuristic criteria for evaluating the quality of predictive power of models are proposed. A sliding regression is used to analyze trends in the development of the Russian banking system after the 1998 crisis.
Date of publication
01.07.2007
Number of purchasers
0
Views
102
Readers community rating
0.0 (0 votes)
Cite Download pdf

To download PDF you should sign in

1

References



Additional sources and materials

Bobyshev A.A. (2001): Tipichnye strategii i finansovoe posrednichestvo. REhSh. Seriya “Luchshie studencheskie raboty”. BSP/01/047.

Golovan' S.V., Karminskij A.M., Kopylov A.V., Peresetskij A.A. (2003): Modeli veroyatnosti defolta rossijskikh bankov. I. Predvaritel'noe razbienie bankov na klastery. Preprint REhSh. WP/2003/039.

Golovan' S.V., Evdokimov M.A., Karminskij A.M., Peresetskij A.A. (2004): Modeli veroyatnosti defolta rossijskikh bankov. II. Vliyanie makroehkonomicheskikh faktorov na ustojchivost' bankov. Preprint REhSh. WP/2004/043.

Peresetskij A.A., Karminskij A.M., Sust A.G.O. van (2004): Modelirovanie rejtingov nadezhnosti rossijskikh bankov // Ehkonomika i mat. metody. T. 40. № 4.

Aldrich J.H., Nelson F.D. (1985): Linear Probability, Logit and Profit Models. Quantitative Applications in the Social Sciences Series № 45. Beverly Hills: SAGE Publications.

Altman E.I. (1968): Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy // J. of Finance. Vol. 23. № 4.

Altman E.I., Marco G., Varetto F. (1994): Corporate Distress Diagnosis: Comparisons using Linear Discriminant Analysis and Neural Networks (the Italian Experience) // J. of Banking and Finance. Vol. 18. № 3.
Altman E.I., Rijken H.A. (2004): How Rating Agencies Achieve Rating Stability // J. of Banking and Finance. Vol. 28. № 11.

Amato J.D., Furfine C.H. (2003): Are Credit Ratings Procyclical? BIS Working Papers. № 129.

Basel-II (2004): Basel Committee on Banking Supervision International Convergence of Capital Measurement and Capital Standards. Bank for International Settlements. June 2004. Http://www.bis.org/publ/bcbs107.htm.

Borio C. (2003): Towards a Macroprudential Framework for Financial Supervision and Regulation? BIS Working Papers. № 128.

Borodovsky M., Peresetsky A. (1994): Deriving Non-homogeneous DNA Markov chain Models by Cluster Analysis Algorithm Minimizing Multiple Alignment Entropy // Computers and Chemistry. Vol. 18. № 3.

Bovenzi J.F., Marino J.A., McFadden F.E. (1983): Commercial Bank Failure Prediction Models // Economic Rev.

Vol. 68 (November 1983). Federal Reserve Bank of Atlanta.

Cole R.A., Gunther J.W. (1995): Separating the Likelihood and Timing of Bank Failure // J. of Banking and Finance. Vol. 19. № 6.

Cole R.A., Gunther J.W. (1998): Predicting Bank Failures: A Comparison of On- and Off-site Monitoring Systems // J. of Financial Services Research. Vol. 13. № 2.

Demirguf-Kunt A., Detragiache E. (1998): The Determinants of Banking Crises in Developed and Developing Countries // IMF Staff Papers. Vol. 45. № 1.

Engelman B., Porath D. (2003): Empirical Comparison of Different Methods for Default Probability Estimation.

Quanteam Research Paper. Http://www.quanteam.de/publications.html.

Espahbodi H., Espahbodi P. (2003): Binary Choice Models and Corporate Takeover // J. of Banking and Finance. Vol. 27. № 4.

Estrella A., Park S., Peristiani S. (2000): Capital Ratios as Predictors of Bank Failure // FRBNY Econ. Policy Rev. Vol. 6. № 2.

Godlewski C. (2004): Are Bank Ratings Coherent with Bank Default Probabilities in Emerging Market Economies?

SSRN. Http://ssrn.com/abstract = 588162.

Gunther J.W., Moore R.R. (2003): Early Warning Models in Real Time // J. of Banking and Finance. Vol. 27. № 10. Jagtiani J., Kolari J., Lemieux C., Shin H. (2003): Early Warning Models for Bank Supervision: Simper Could be Better // Econ. Perspectives. Vol. 27. № 3. Federal Reserve Bank of Chicago.

Kolari J., Glennon D., Shin H., Caputo M. (2002): Predicting Large US Commercial Bank Failures // J. of Econ. and Business. Vol. 54. № 4.

Komulainen T., Lukkarila J. (2003): What Drives Financial Crises in Emerging Markets? // Emerging Markets Rev. Vol. 4. № 3.

Korobow L., Stuhr D.P. (1983): The Relevance of Peer Groups in Early Warning Analysis // Econ. Rev. Vol. 68 (November 1983). Federal Reserve Bank of Atlanta.

Lawrence C.L., Smith L.D., Rhoades M. (1992): An Analysis of Default Risk in Mobile Home Credit // J. of Banking and Finance. Vol. 16. № 2.

Lennox C. (1999): Identifying Failing Companies: a Reevaluation of the Logit, Probit and DA Approaches // J. of Econ. and Business. Vol. 51. № 4.

Loffler G. (2004): An Anatomy of Rating Through the Cycle // J. of Banking and Finance. Vol. 28. № 3.

Martin D. (1977): Early Warning of Bank Failure: A Logit Regression Approach // J. of Banking and Finance. Vol. 1. № 3.

Mathe C., Peresetsky A., Dehais P., Montagu van M., Rouze P. (1999): Classification of Arabidopsis Thaliana Gene Sequences: Clustering of Coding Sequences into Two Groups According to Codon Usage Improves Gene Prediction // J. of Molecular Biology. Vol. 285. № 5.

Marchesini R., Perdue G., Bryan V. (2004): Applying Bankruptcy Prediction Models to Distressed High-yield Bond Issues. // J. of Fixed Income. Vol. 13. № 4.

Ohlson J.A. (1980): Financial Ratios and the Probabilistic Prediction of Bankruptcy // J. of Accounting Res. Vol. 18. № 1.

Peresetsky A., Karminsky A., Golovan S. (2004): Probability of Default Models of Russian Banks. Bank of Finland BOFIT Discussion Paper № 21/2004.

Sahajwala R., Bergh van den P. (2000): Supervisory Risk Assessment and Early Warning Systems. Basel Committee on Banking Supervision. Working Paper 4.

Scott A.J., Wild C.J. (1986): Fitting Logistic Models under Case-control or Choice-based Sampling // J. of the Royal Stat. Society. Series B. Vol. 48. № 2.

Segoviano M.A., Lowe P. (2002): Internal Ratings, the Business Cycle and Capital Requirements: Some Evidence from an Emerging Market Economy. BIS Working Papers. № 117.

Soest van A.H.O., Peresetsky A.A., Karminsky A.M. (2003): An Analysis of Ratings of Russian Banks. Tilburg University Center. Discussion Paper. Series. № 2003/85.
Stone M., Rasp J. (1991): Tradeoffs in the Choice between Logit and OLS for Accounting Choice Studies // Accounting Rev. Vol. 66. № 1.

Wescott S.H. (1984): Accounting Numbers and Socioeconomic Variables as Predictors of Municipal General Obligation Bond Ratings // J. of Accounting Res. Vol. 22. № 1.

Westgaards S., Wijst van der N. (2001): Default Probabilities in a Corporate Bank Portfolio: A Logistic Model Approach // European J. of Operational Res. Vol. 135.

Wiginton J.C. (1980): A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behaviour // J. of Financial and Quantitative Analysis. Vol. 15. № 3.